Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Personal Interview

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Telephone Interview

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

This dataset collection contains data from the South African General Household Survey (GHS) conducted annually by Statistics South Africa (Stats SA) from 2012 to 2022. The GHS is a critical tool for monitoring and evaluating various aspects of living conditions and service delivery across South African households.

Key Features:

Time Span: 2012 to 2022 Geographical Coverage: Nationwide, covering all provinces in South Africa Sample Size: Thousands of households each year Data Scope: The datasets include a wide range of variables such as employment status, education, health, housing, access to services, social grants, and more.

These datasets are invaluable for researchers, policymakers, and analysts interested in understanding socio-economic trends, evaluating public policies, or conducting longitudinal studies on living conditions in South Africa. They can be used for time series analysis, predictive modeling, and other data-driven inquiries.

Abstract

The General Household Survey (GHS) has been used as an instrument to track the progress of development since 2002 when it was first introduced . It is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National

Analysis unit

Households

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus, version numbers of files within a dataset may not match.

Abstract

The GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, employment, health, housing and household access to services.

Geographic coverage

The survey is representative at national level and at provincial level.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data

Sampling procedure

The sample design for the GHS 2011 was based on a master sample (MS) that was originally designed for the Quarterly Labour Force Survey (QLFS) and was used for the first time for the GHS in 2008. This master sample is shared by the QLFS, GHS, Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Surveys (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.

Mode of data collection

Face-to-face [f2f]

Research instrument

GHS uses questionnaires as data collection instruments

Data appraisal

In GHS 2009-2015:

The variable on land size in the General Household Survey questionnaire for 2009-2015 should be used with caution. The data comes from questions on the households' agricultural activities in Section 8 of the GHS questionnaire: Household Livelihoods: Agricultural Activities. Question 8.8b asks:

“Approximately how big is the land that the household use for production? Estimate total area if more than one piece.” One of the response category is worded as:

1 = Less than 500m2 (approximately one soccer field)

However, a soccer field is 5000 m2, not 500, therefore response category 1 is incorrect. The correct category option should be 5000 sqm. This response option is correct for GHS 2002-2008 and was flagged and corrected by Statistics SA in the GHS 2016.

Abstract

Stats SA conducted the October Household Survey (OHS) annually from 1994 to 1999, based on a probability sample of a large number of households ranging from 16 000 to 30 000 households each year (depending on availability of funding). This survey was discontinued in 1999 due to the reprioritisation of surveys in the face of financial constraints. February 2000 saw the birth of the Labour Force Survey (LFS), which is a biannual survey conducted by Stats SA in March and September of each year. The LFS covers some areas previously covered by the OHS, but not all, since it is a specialised survey principally designed to measure the dynamics in the labour market. The September LFS each year does include a section designed to measure social indicators such as access to infrastructure, but again this section does not go into as much depth as the OHS used to. A need was therefore identified by our users for a regular survey designed specifically to measure the level of development and the performance of government programmes and projects. The General Household Survey (GHS) was developed for this purpose. While the survey replaces the October Household Survey (OHS), the indicators measured in the 13 nodal areas identified for the Integrated Rural Development Strategy (IRSD) formed the basis for the subject matter of the survey. The first round of the GHS was conducted in July 2002 and the second round in July 2003.

Geographic coverage

The scope of the General Household Survey 2003 was national coverage.

Analysis unit

The units of anaylsis for the General Household Survey 2003 are individuals and households.

Universe

The survey covered all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as students' hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the GHS 2003 a multi-stage stratified sample was drawn using probability proportional to size principles.

The sample was drawn from the master sample, which Statistics South Africa uses to draw samples for its regular household surveys. The master sample is drawn from the database of enumeration areas (EAs) established during the demarcation phase of Census 1996. As part of the master sample, small EAs consisting of fewer than 100 households are combined with adjacent EAs to form primary sampling units (PSUs) of at least 100 households, to allow for repeated sampling of dwelling units within each PSU. The sampling procedure for the master sample involves explicit stratification by province and within each province, by urban and non-urban areas. Within each stratum, the sample was allocated disproportionately. A PPS sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 000 PSUs were selected. In each selected PSU a systematic sample of ten dwelling units was drawn, thus, resulting in approximately 30 000 dwelling units. All households in the sampled dwelling units were enumerated. The master sample is divided into five independent clusters. In order to avoid respondent fatigue (the LFS is a rotating panel survey which is conducted twice yearly), the GHS sample uses a different cluster from the LFS clusters.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GHS 2003 questionnaire collected data on: Household characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production Individuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, disability, access to social services, mortality. Women's characteristics: fertility

Response rate

Response codes Number of responses % Completed 26 469 84.7 Non-contact 897 2.9 Refusal 645 2.1 Partly completed 18 0.1 Unusable information 1 0.0 Vacant 1 510 4.8 Listing error 246 0.8 Other 1 447 4.6 Total 31 233 100.0

The GHS is an annual household survey, specifically designed to measure various aspects of the living circumstances of South African households. The key findings reported here focus on the five broad areas covered by the GHS, namely: education, health, activities related to work and unemployment, housing and household access to services and facilities.

Abstract

The GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey 2014 had national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data

Sampling procedure

The sample design for the GHS 2014 was based on a master sample (MS) that was originally designed for the Quarterly Labour Force Survey (QLFS) and was used for the first time for the GHS in 2008. This master sample is shared by the QLFS, GHS, Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Survey (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire

Data appraisal

GHS 2009-2015: The variable on land size in the General Household Survey questionnaire for 2009-2015 should be used with caution. The data comes from questions on the households' agricultural activities in Section 8 of the GHS questionnaire: Household Livelihoods: Agricultural Activities. Question 8.8b asks: “Approximately how big is the land that the household use for production? Estimate total area if more than one piece.” One of the response category is worded as: 1 = Less than 500m2 (approximately one soccer field) However, a soccer field is 5000 m2, not 500, therefore response category 1 is incorrect. The correct category option should be 5000 sqm. This response option is correct for GHS 2002-2008 and was flagged and corrected by Statistics SA in the GHS 2016.

GHS 2014-2018 and from GHS 2021 onwards: The person data file in has two Employment Status variables in the GHS. According to the Statistics SA documentation, both these variables are derived from the variables LAB1 and LAB12. But the value “Unspecified” in the variable employ_Status1 becomes “Not Economically Active” in the variable employ_Status2. There is no clear explanation for this change. Statistics SA has been contacted for further information on these variables.

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Abstract

The GHS replaced the October Household Survey (OHS) which was introduced in 1993 and was terminated in 1999. The survey is an omnibus household-based instrument aimed at determining the progress of development in the country. It measures, on a regular basis, the performance of programmes as well as the quality of service delivery in a number of key service sectors in the country. The GHS covers six broad areas, namely education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National

Analysis unit

Households

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data [ssd]

Sampling procedure

The General Household Survey (GHS) uses the Master Sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with the GHS. The GHS 2015 collection was based on the 2013 Master Sample. This Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103,576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3,324 primary sampling units (PSUs) in the Master Sample with an expected sample of approximately 33,000 dwelling units (DUs). The number of PSUs in the current Master Sample (3,324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3,080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates.

The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro. The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. Caution must be exercised when interpreting the results of the GHS at low levels of disaggregation. The sample and reporting are based on the provincial boundaries as defined in December/January 2006. These new boundaries resulted in minor changes to the boundaries of some provinces, especially Gauteng, North West, Mpumalanga, Limpopo, Eastern Cape and Western Cape. In previous reports the sample was based on the provincial boundaries as defined in 2001, and there will therefore be slight comparative differences in terms of provincial boundary definitions.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The questionnaires were scanned and processed. Editing and imputation was done using a combination of manual and automated editing procedures.

Response rate

Average response rate of 99 percent

Data appraisal

A comprehensive detail about the editing process can be found in the GHS 2015 report (P0318) attached to the external resources.

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

The main purpose of the General Household Survey (GHS) is to measure the level of development and performance of various government programmes and projects. This report specifically aims at providing national indicators on various living conditions such as access to services and facilities, education and health, for 2002. It also draws comparisons between the GHS 2002 results and the Census 2001 results. A multi-stage stratified sample was drawn to run the GHS in 2002. In the initial stages, probability proportional to size principles were applied. The first stage was stratification by province, then by type of area within each province (urban or non-urban). Primary sampling units (PSUs) were then selected within each stratum. The smaller provinces were given a disproportionately large number of PSUs compared to the bigger provinces. Systematic sampling was then applied within each PSU to select 10 dwelling units (including units in hostels), as ultimate sampling units. All households at the selected dwelling units were interviewed. A sample comprised 30 000 dwelling units. Out of these, 1 313 dwelling units were found to be out of scope. Of the valid dwelling units, 3 439 households did not respond and 26 287 responded. There are 4 data files. House data: 26, 243 cases (and records); Person data: 102, 461 cases (and records); Stratum_psu (Stratum and PSU numbers): 2, 972 cases (and records); Worker data: 69, 585 cases (and records).

The GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Abstract

The GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households Individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Données échantillonées [ssd]

Sampling procedure

A multi-stage, stratified random sample was drawn using probability-proportional-to-size principles. Firstlevel stratification was based on province and second-tier stratification on district council. Field staff employed and trained by Stats SA visited all the sampled dwelling units in each of the nine provinces.During the first phase of the survey, sampled dwelling units were visited and informed about the coming survey as part of the publicity campaign.

The GHS 2009 represents the second year of a new master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES). The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income. Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: • Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); • EAs with fewer than 25 DUs were excluded; • EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; • Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and • Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire · The Cover page contains particulars of households, response details, field staff information, result codes, etc. (This information is not contained in the data supplied) · The Flap covers demographic information (name, sex, age, population group, etc.) · Section 1 covers biographical information (education, health, disability, welfare) · Section 2 covers non-remunerated trips undertaken in the 12 months prior to the survey. · Section 3 and 4, this sections covers Household information (type of dwelling, ownership of dwelling and other assets, electricity, water and sanitation, environmental issues, services, transport, expenditure etc.

Response rate

25361 Housholds of 32636 were successfully interviewed (77.7% as response rate)

Abstract

The GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households Individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Données échantillonées [ssd]

Sampling procedure

The sample design for the GHS 2011 was based on a master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: · Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); · EAs with fewer than 25 DUs were excluded; · EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; · Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and · Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

For more Information on sampling please view technical notes in the statistical release

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire - Cover page: Household information, response details, field staff information, result codes, etc. - Flap: Demographic information (name, sex, age, population group, etc.) - Section 1: Biographical information (education, health, disability, welfare) - Section 2: Economic activities - Section 3:Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation,environmental issues, services, transport, etc.) - Section 4: Food security, income and expenditure (food supply, agriculture, expenditure, etc.)

Response rate

The national response rate for the survey was 94,2%.

Abstract

The National Income Dynamics Study (NIDS) is a face-to-face longitudinal survey of individuals living in South Africa as well as their households. The survey was designed to give effect to the dimensions of the well-being of South Africans, to be tracked over time. At the broadest level, these were:

· Wealth creation in terms of income and expenditure dynamics and asset endowments · Demographic dynamics as these relate to household composition and migration · Social heritage, including education and employment dynamics, the impact of life events (including positive and negative shocks), social capital and intergenerational developments · Access to cash transfers and social services

Geographic coverage

National

Analysis unit

Households

Universe

The target population for NIDS was private households in all nine provinces of South Africa, and residents in workers' hostels, convents and monasteries. The frame excludes other collective living quarters, such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified, two-stage cluster sample design was employed in sampling the Dwelling units to be included in the base wave. In the first stage, a sample of 400 Primary Sampling Units (psus)2 was drawn (by statisticians at Stats SA) from Stats SA's 2003 Master Sample of 3000 psus. At the time that the 2003 Master Sample was compiled, eight non-overlapping samples of ten or twelve dwelling Units were systematically drawn within each PSU. Each of these samples is termed A “cluster” by Stats SA. These clusters were then allocated to the various household Surveys that were conducted by Stats SA between 2004 and 2007 (such as the Labour Force Surveys, General Household Surveys and the 2005/06 Income and Expenditure Survey). However, two clusters in each PSU were never used by Stats SA and these were allocated to NIDS.

In the first stage, a sample of 400 PSUs had to be drawn from the 3000 PSUs in the Master Sample. The explicit strata in the Master Sample are the 53 district councils (DCs). The sample was proportionally allocated to these 53 strata and PSUs were selected within strata with probability proportional to size. It should be noted that the sample was not designed to be representative at provincial level, implying that analysis of the results at the province level is not recommended.

Mode of data collection

Face-to-face [f2f]

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

In 2005, Stats SA undertook a major revision of the Labour Force Survey (LFS) which had been conducted twice per year since 2000. This revision resulted in changes to the survey methodology, the survey questionnaire, the frequency of data collection and data releases, and the survey data capturing and processing systems. The redesigned labour market survey, the QLFS, is now the principal vehicle for collecting labour market information on a quarterly basis.

This report is the fifth annual report produced by Stats SA on the labour market in South Africa. The analysis is based on annual labour market results from 2007 to 2012. The report also includes a statistical appendix with historical data dating back to 2007 on an annual basis. The 2012 annual report introduces for the first time an analysis of labour market dynamics (discussed in Chapter 2). The report also includes four specialised features as follows: government job creation programmes (Chapter 4); migration (Chapter 6); the labour market from a census perspective (Chapter 9); and, other forms of work (Chapter 10).

Objective The objective of this report is twofold: first, to present annual labour market data backcast to 2007, and second, to analyse important aspects of the labour market in South Africa over the past five years.

Data sources Labour Force Survey –2007 (March and September) QLFS – 2008 to 2012 (Quarters 1 to 4) Time Use Survey, 2010 Volunteer Activities Survey, 2010 Census 1996; Census 2011

Geographic coverage

the nine provinces of South Africa

Analysis unit

Individuals

Universe

Households in the nine provinces of South Africa

Kind of data

Données échantillonées [ssd]

Sampling procedure

The Labour Force Survey and the Quarterly Labour Force Survey are based on a Master Sample and there have been three of them so far. The design of each is outlined below.

1999 Master Sample For the LFSs of February 2000 to March 2004, a rotating panel sample design was used to allow for measurement of change in people's employment situation over time. The same dwellings were visited on, at most, five different occasions. After this, new dwelling units were included for interviewing from the same PSU in the master sample. This means a rotation of 20% of dwelling units each time. The database of enumerator areas (EAs) established during the demarcation phase of Census '96 constituted the sampling frame for selecting EAs for the LFS. Small EAs consisting of fewer than 100 dwelling units were combined with adjacent EAs to form primary sampling units (PSUs) of at least 100 dwelling units, to allow for repeated sampling of dwelling units within each PSU. The sampling procedure for the master sample involved explicit stratification by province and within each province, by urban and non-urban areas (Census 1996 definitions). Independent samples of PSUs were drawn for each stratum within each province. The smaller provinces were given a disproportionately large number of PSUs compared to the bigger provinces. Simple random sampling was applied to select 10 dwelling units to visit in each PSU as ultimate sampling units. If more than one household was found in the same dwelling unit all such households were interviewed.

2004 Master Sample The 2004 Master Sample was used in the LFSs of September 2004 to September 2007. Enumeration Areas (EAs) that had a household count of less than twenty-five were omitted from the census frame that was used to draw the sample of PSUs for the Master Sample. Other omissions from the frame included all institution EAs except workers' hostels, convents and monasteries. EAs in the census database that were found to have less than sixty dwelling units during listing were pooled. This Master Sample was a multi-stage stratified sample. The overall sample size of PSUs was 3 000. The explicit strata were the 53 district councils. The 3 000 PSUs were allocated to these strata using the power allocation method. The PSUs were then sampled using probability proportional to size principles. The measure of size used was the number of households in a PSU as counted in the census. The sampled PSUs were listed with the dwelling unit as the listing unit. From these listings systematic samples of dwelling units per PSU were drawn. These samples of dwelling units formed clusters. The size of the clusters differed depending on the specific survey requirements. The LFS used one of the clusters that contained ten dwelling units.

Current Master Sample The Quarterly Labour Force Survey (QLFS) frame has been developed as a general-purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30 000 dwellings per quarter.

The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for the 2001 Census, the country was divided into 80 787 enumeration areas (EAs). Stats SA's household-based surveys use a master sample of primary sampling units (PSUs) which comprises EAs that are drawn from across the country.

The sample is designed to be representative at provincial level and within provinces at metro/nonmetro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal. This implies, for example, that within a metropolitan area the sample is representative at the different geography types that may exist within that metro.

The current sample size is 3 080 PSUs. It is divided equally into four subgroups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

The sample for the redesigned Labour Force Survey (i.e. the QLFS) is based on a stratified twostage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

Sample rotation Each quarter, a ¼ of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings will remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, say two quarters and a new household moves in then the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (unoccupied).

Mode of data collection

Interview face à face [f2f]

Research instrument

the questionnaire of QLFS is composed by 5 sections: - Section1, Biographical information (marital status, language, migration, education, training, literacy, etc.)
- Section2, Economic activities in the last week : The questions in this section determine those individuals, aged 15-64 years, who are employed and those who are not employed.
- Section 3, Unemployment and economic inactivity : This section determines which respondents are unemployed and which respondents are not economically active. - Section 4, Main work activities in the last week : This section contains questions about the work situation of respondents who are employed. It includes questions about the number of jobs at which the respondent works, the hours of work, the industry and occupation of the respondent as well as whether or not the person is employed in the formal or informal sector etc., - Section 5 covers earnings in the main job for employees and own-account workers aged 15 years and above.

Abstract

The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).

Geographic coverage

National

Analysis unit

• Households • Individuals • Agricultural plots • Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.

After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.

The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.

Sampling deviation

Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.

The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.

The Community Questionnaire collected prices during both visits, and different community level information during the two visits.

Cleaning operations

CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

Response

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.